Ischaemic stroke on anticoagulation therapy and early recurrence in acute cardioembolic stroke: the IAC study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A subset of ischaemic stroke patients with atrial fibrillation (AF) have ischaemic stroke despite anticoagulation. We sought to determine the association between prestroke anticoagulant therapy and recurrent ischaemic events and symptomatic intracranial haemorrhage (sICH). METHODS: We included consecutive patients with acute ischaemic stroke and AF from the Initiation of Anticoagulation after Cardioembolic stroke (IAC) study from eight comprehensive stroke centres in the USA. We compared recurrent ischaemic events and delayed sICH risk using adjusted Cox regression analyses between patients who were prescribed anticoagulation (ACp) versus patients who were naïve to anticoagulation therapy prior to the ischaemic stroke (anticoagulation naïve). RESULTS: Among 2084 patients in IAC, 1518 had prior anticoagulation status recorded and were followed for 90 days. In adjusted Cox hazard models, ACp was associated with some evidence of a higher risk higher risk of 90-day recurrent ischaemic events only in the fully adjusted model (adjusted HR 1.50, 95% CI 0.99 to 2.28, p=0.058) but not increased risk of 90-day sICH (adjusted HR 1.08, 95% CI 0.46 to 2.51, p=0.862). In addition, switching anticoagulation class was not associated with reduced risk of recurrent ischaemic events (adjusted HR 0.41, 95% CI 0.12 to 1.33, p=0.136) nor sICH (adjusted HR 1.47, 95% CI 0.29 to 7.50, p=0.641). CONCLUSION: AF patients with ischaemic stroke despite anticoagulation may have higher recurrent ischaemic event risk compared with anticoagulation-naïve patients. This suggests differing underlying pathomechanisms requiring different stroke prevention measures and identifying these mechanisms may improve secondary prevention strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".